At the quantum level

Zheng-Xin Liu, Xiao-Ting Zhou, Xin Liu +2 more

The topological properties of adiabatic gauge fields for multi-level (three-level in particular) quantum systems are studied in detail. Similar to the result that the adiabatic gauge field for SU (2) systems (e.g. two-level quantum system or angular momentum systems, etc) has a monopole structure, the curvature 2-forms of the adiabatic holonomies for SU (3) three-level and SU (3) eight-level quantum systems are shown to have monopole-like (for all levels) or instanton-like (for the degenerate levels) structures.

David Gevaux

Edward James Anderson

Barry C. Sanders, Gerard J Milburn

In a three-level ssv-type atom, which has two excited levels and a ground level, the fluorescence exhibits quantum beats due to a correlation between the two excited levels. However, a measurement of the atomic level yields information about the atomic state but completely suppresses the quantum beats. Here we discuss a modification of the atomic-level measurement to allow for a continuous transition from perfect quantum beats to complete information of the atomic level. The complementary relation between the beats and knowledge of the atomic level is quantitatively shown to be a proportionality between the beat visibility and the probability of making an incorrect measurement of the atomic level. We discuss the realization of the scheme in the context of current experimental proposals involving atomic-level measurements via Fock number states in micromaser cavities. Imperfect photodetector efficiency and micromaser cavity damping are incorporated into the formalism.

Jincheng Zhang

Quantum degradation processes in complex systems are increasingly recognized as multi-level phenomena, deviating from traditional single-level models. This research introduces an adaptive multi-level quantum degradation model utilizing deep neural networks to capture the intricate dynamics of quantum system decay across multiple levels. The core claim posits that quantum degradation is not a singular event but a coordinated effect of multiple levels. The proposed model dynamically adjusts its parameters based on learned features, simulating the system's evolution over various timescales. The key mechanism involves training a deep neural network to identify and characterize degradation features at each level. The model's output, represented as (Qt), reflects the quantum state at time *t*, where Qt = (q1,t, q2,t, ..., qK,t), and *K* represents the number of levels in the system. The model's adaptive nature allows it to account for the varying degrees of degradation at each level, providing a more realistic and accurate representation of quantum decay compared to conventional single-level approaches. This work addresses a critical gap in current quantum degradation modeling techniques.